Current genetic and molecular-based methodologies for identification of biological threat organisms from complex environmental backgrounds lack the capability for rapid reagentless broad based detection. This unmet, military and societal need stems from the 2001 anthrax attack, in which letters containing anthrax spores were mailed to two United States Senators and several news offices.
Conventional means of identifying pathogens using biology tools such as specific antibodies, genetic markers or propagation in culture are fundamentally slow and require significant hands-on manipulations. Most detection strategies require long sample preparations and extractions that precede analysis and many techniques require expensive reagents that are agent specific. Furthermore, as new Biological Warfare Agents (BWAs) and Chemical Warfare Agents (CWAs) are engineered, these conventional tools are likely to become less and less effective. Therefore, there is an increasing need to have methods that can rapidly and accurately detect and classify small amounts of these agents at a molecular level without coming into contact with them. Methods are also needed to help expand our understanding of the biological and chemical basis of such warfare agents and the potential impact on the human body. Furthermore, the knowledge gained through such molecular analysis helps identify new targets for therapeutic and preventative agents.
One approach that may prove beneficial is the use of multiple data types in detecting and identifying unknown materials, and specifically pathogenic microorganisms. However, the challenge of integrating multiple data types into a comprehensive database searching algorithm has yet to be adequately solved. Existing data fusion and database searching algorithms used in the spectroscopic community suffer from key disadvantages. Most notably, competing methods such as interactive searching are not scalable, and are at best semi-automated, requiring significant user interaction. For instance, the BioRAD KnowItAll® software claims an interactive searching approach that supports searching up to three different types of spectral data using the search strategy most appropriate to each data type. Results are displayed in a scatter plot format, requiring visual interpretation and restricting the scalability of the technique. Also, this method does not account for mixture component searches. Data Fusion Then Search (DFTS) is an automated approach that combines the data from all sources into a derived feature vector and then performs a search on that combined data. The data is typically transformed using a multivariate data reduction technique, such as Principle Component Analysis, to eliminate redundancy across data and to accentuate the meaningful features. This technique is also susceptible to poor results for mixtures, and it has limited capacity for user control of weighting factors.
The present disclosure describes a system and method that overcomes these disadvantages allowing users to identify unknown materials by using multiple spectroscopic data. More specifically, the present disclosure provides systems and methods to detect and identify pathogenic microorganisms using fused sensor data.
Some of the spectroscopic data that may be fused include but are not limited to Raman, infrared, and fluorescence spectroscopic data. Raman spectroscopy provides information about the vibrational state of molecules. Many molecules have atomic bonds capable of existing in a number of vibrational states. Such molecules are able to absorb incident radiation that matches a transition between two of its allowed vibrational states and to subsequently emit the radiation. Most often, absorbed radiation is re-radiated at the same wavelength, a process designated Rayleigh or elastic scattering. In some instances, the re-radiated radiation can contain slightly more or slightly less energy than the absorbed radiation (depending on the allowable vibrational states and the initial and final vibrational states of the molecule). The result of the energy difference between the incident and re-radiated radiation is manifested as a shift in the wavelength between the incident and re-radiated radiation, and the degree of difference is designated the Raman shift (RS), measured in units of wavenumber (inverse length). If the incident light is substantially monochromatic (single wavelength) as it is when using a laser source, the scattered light which differs in frequency can be more easily distinguished from the Rayleigh scattered light. An apparatus for Raman Chemical Imaging (RCI) has been described by Treado in U.S. Pat. No. 6,002,476, and in U.S. patent application Ser. No. 09/619, 371, now U.S. Pat. No. 6,788,860, the entirety of which is incorporated herein by reference.
Raman analysis is a vibrational spectroscopy technique that has been employed successfully as a rapid reagentless technique for the detection of microorganisms. Raman sensitivities can be on the cellular level, and the Raman specificity can be at the subspecies level. Applications of Raman spectroscopy to clinical samples have been achieved with various different enhancement techniques. The real advantage of Raman spectroscopy was achieved when digital imaging was coupled with Raman spectroscopy to allow for visualization of the molecular environment of a sample.
In fluorescence spectroscopy, photons are emitted from a material following an excitation step in which absorption of photons occurs. Experiments typically include a polychromatic excitation source such as mercury (Hg) or xenon (Xe) lamps or a monochromatic source such as a laser for sample excitation. A portion of the emitted radiation may then be directed into a dispersive monochromator to which a detector device such as a CCD is attached. By measuring the fluorescence spectrum from a material, one can deduce qualitative and quantitative information from inorganic and organic species.
Molecular UV/visible and infrared (IR) absorption spectroscopies involve the absorption of photons throughout the UV/visible and infrared spectral regions. Typical instrumentation includes a polychromatic source such as a deuterium or quartz tungsten halogen lamp, a dispersive element such as a monochromator or interferometer and a detection device such as a Si CCD or InGaAs focal plane array detector. Absorption measurements based upon UV-visible or IR radiation find a wide number of applications for both qualitative and quantitative determination of inorganic and organic species.
Spectroscopic imaging combines digital imaging and molecular spectroscopy techniques which can include Raman scattering, fluorescence, photoluminescence, ultraviolet, visible and infrared absorption spectroscopies. When applied to the chemical analysis of materials, spectroscopic imaging is commonly referred to as chemical imaging.
In many respects, Raman chemical imaging is an extension of Raman spectroscopy. Raman chemical imaging combines Raman spectroscopy and digital imaging for the molecular-specific analysis of materials. Much of the imaging performed since the development of the first Raman microprobes has involved spatial scanning of samples beneath Raman microprobes in order to construct Raman “maps” of surfaces. Historically, Raman imaging systems, have been built using this so called flying spot (“point scanning”) approach, where a laser beam is focused to a spot and is scanned over the object field, or likewise a line scanning approach, where the laser spot is broadened in one direction by, for example, a cylindrical lens, and the two dimensional image formed on a CCD array has one spatial dimension and one wavelength dimension. Raman chemical imaging techniques have only recently achieved a degree of technological maturity that allows the simultaneous collection of high-resolution (spectral and spatial) data. Advancements in imaging spectrometer technology and their incorporation into microscopes that employ CCDs, holographic optics, lasers, and fiber optics have allowed Raman chemical imaging to become a practical technique for material analysis.
ChemImage's FALCON™ Raman chemical imaging microscope employs fluorescence imaging as the trigger mechanism to identify the presence of biological material and wide field illumination Raman collection optics with digital imaging detection for identification of the biologicals. An apparatus for Raman Chemical Imaging (RCI) has been described by Treado in U.S. Pat. No. 6,002,476, and U.S. Pat. No. 6,788,860, the entirety of each of which are incorporated herein by reference.